Biology subjects

Lorenz, H.-M.

Publications and source records attributed to Lorenz, H.-M..

6 recordsLinked to original sources

bioRxiv2025

Deep learning predicts tissue outcomes in retinal organoids

Retinal organoids have become important models for studying development and disease, yet stochastic heterogeneity in the formation of cell types, tissues, and phenotypes remains a major challenge. This limits our ability to precisely experimentally address the early developmental trajectories towards these outcomes. Here, we utilize deep learning to predict the differentiation path and resulting tissues in retinal organoids well before they become visually discernible. Our approach effectively bypasses the challenge of organoid-related heterogeneity in tissue formation. For this, we acquired a high-resolution time-lapse imaging dataset comprising about 1,000 organoids and over 100,000 images enabling precise temporal tracking of organoid development. By combining expert annotations with advanced image analysis of organoid morphology, we characterized the heterogeneity of the retinal pigmented epithelium (RPE) and lens tissues, as well as global organoid morphologies over time. Using this training set, our deep learning approach accurately predicts the emergence and size of RPE and lens tissue formation on an organoid-by-organoid basis at early developmental stages, refining our understanding of when early lineage decisions are made. This approach advances knowledge of tissue and phenotype decision-making in organoid development and can inform the design of similar predictive platforms for other organoid systems, paving the way for more standardized and reproducible organoid research. Finally, it provides a direct focus on early developmental time points for in-depth molecular analyses, alleviated from confounding effects of heterogeneity.

developmental biology↗

bioRxiv2024

Accurate, fast and memory efficient quantification of immune cell phenotypes in cytometry using machine learning

To achieve accurate and reproducible cytometry data analysis, we benchmarked 19 machine learning algorithms for supervised and unsupervised cell classification. The underlying data encompassed 138 million cells from seven independent datasets including conventional flow cytometry, spectral flow cytometry and mass cytometry. We found that tree-based classifiers and in particular Decision Trees, outperformed other approaches in classification accuracy, speed and memory use. High accuracy was achieved even for cell populations rarer than 1% using decision trees. We validated our decision tree-based approach in a clinical setting using diagnostic blood T cell phenotyping of 107 patients. Automatic quantification of CD4 helper T cell phenotypes achieved 99 % accuracy compared to manual expert assessment. Finally, we combined automated data transformation, supervised and unsupervised gating, an application program interface and a user-friendly desktop-application into FACSPy and FACSPyUI, a fast and scalable open-source toolbox for the analysis and visualization of cytometry data.

bioinformatics↗

bioRxiv2024

CytoNormPy enables a fast and scalable removal of batch effects in cytometry datasets.

MotivationWe present a python implementation of the widely used CytoNorm algorithm for the removal of batch effects. ResultsOur implementation ran up to 85% faster than its R counterpart, while being fully compatible with common single-cell data structures and -frameworks of python. We extend the previous functionality by adding common clustering algorithms and provide key visualizations of the algorithm and its evaluation. Availability and implementationThe CytoNormPy implementation is freely available on GitHub: https://github.com/TarikExner/CytoNormPy.

bioinformatics↗

bioRxiv2023

Systemic Lupus Erythematosus Serum Stimulation of Human Intestinal Organoids Induces Changes in Goblet Cell Differentiation and Mitochondrial Fitness

Human intestinal epithelial cells are the interface between potentially harmful luminal content and basally residing immune cells. Their role is not only nutrient absorption but also the formation of a tight monolayer that constantly secrets mucus creating a multi-layered protective barrier. Alterations in this barrier can lead to increased gut permeability which is frequently seen in individuals with chronic extraintestinal autoimmune diseases, such as Systemic Lupus Erythematosus (SLE). Despite recent advances in identifying alterations in gut microbiota composition in SLE patients, not much attention has been given to the epithelial barrier itself. To date, it remains largely unexplored which role and function intestinal epithelial cells have in SLE pathology. Here, we present a unique near-physiologic in vitro model specifically designed to examine the effects of SLE on the epithelial cells. We utilize human colon organoids that are stimulated with serum obtained from SLE patients. Combining bulk and scRNA transcriptomic analysis with functional assays revealed that SLE serum stimulation induced a unique expression profile marked by a type I interferon gene signature. Additionally, organoids exhibited decreased mitochondrial fitness, alterations in mucus composition and imbalanced cellular composition. Similarly, transcriptomic analysis of SLE human colon biopsies revealed a downregulation of epithelial secretory markers. Our work uncovers a crucial connection between SLE and intestinal homeostasis that might be promoted in vivo through the blood, offering insights into the causal connection of barrier dysfunction and autoimmune diseases.

cell biology↗

bioRxiv2022

Human and murine neutrophils share core transcriptional programs in both homeostatic and inflamed contexts

Neutrophils are frequently studied in murine models, but the extent to which findings translate to humans remains poorly defined. Here, we performed an integrative transcriptomic analysis of 11 murine and 13 human datasets. In homeostasis, neutrophils exhibited the highest number of lineage-specific genes and the greatest degree of correlated expression among genes with one-to-one orthologs (r = 0.79, P < 2.2 x 10-16) compared to other leukocytes. In inflammation, neutrophils displayed considerable transcriptional diversity, but shared a core inflammation program across a broad range of conditions which was conserved between species. This core program included genes encoding IL-1 family members, CD14, IL-4R, CD69 and PD-L1. Chromatin accessibility of core inflammation genes increased significantly in blood compared to bone marrow and further with migration from blood to tissue. Transcription factor enrichment analysis nominated members of the NF-{kappa}B family and AP-1 complex as important drivers of the core inflammation program, and HoxB8 neutrophils with JUNB knockout showed a significantly reduced expression of core inflammation genes at baseline and upon stimulation. In vitro perturbations confirmed surface protein upregulation of core inflammation members in both species. Together, we demonstrate substantial transcriptional conservation in neutrophils in homeostasis and identify a core inflammation program conserved across species. This systems biology approach can be leveraged to improve transitions between the murine and human context. Key PointsO_LIThe transcriptome of resting neutrophils is substantially conserved between humans and mice C_LIO_LIA core inflammation program in neutrophils is shared across a broad range of conditions and conserved across humans and mice C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=52 SRC="FIGDIR/small/516246v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1f6b40borg.highwire.dtl.DTLVardef@1a67bb4org.highwire.dtl.DTLVardef@1039a8forg.highwire.dtl.DTLVardef@1982d10_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2021

Aging and interferon gamma response drive the phenotype of neutrophils in the inflamed joint

ObjectivesNeutrophils are typically the most abundant leukocyte in arthritic synovial fluid. We sought to understand changes that occur in neutrophils as they migrate from blood to joint. MethodsWe performed RNA sequencing of neutrophils from healthy human blood, arthritic blood, and arthritic synovial fluid, comparing transcriptional signatures with those from murine K/BxN serum transfer arthritis. We employed mass cytometry to quantify protein expression and sought to reproduce the synovial fluid phenotype ex vivo in cultured healthy blood neutrophils. ResultsBlood neutrophils from healthy donors and patients with active arthritis exhibited largely similar transcriptional signatures. By contrast, synovial fluid neutrophils exhibited more than 1,600 differentially expressed genes. Gene signatures identified a prominent response to interferon gamma (IFN{gamma}), as well as to tumor necrosis factor, interleukin 6, and hypoxia, in both humans and mice. Mass cytometry also found healthy and arthritic donor blood neutrophils largely indistinguishable but revealed a range of neutrophil phenotypes in synovial fluid defined by downregulation of CXCR1 and upregulation of Fc{gamma}RI, HLA-DR, PD-L1, ICAM-1 and CXCR4. Reproduction of key elements of this signature in cultured blood neutrophils required both IFN{gamma} and prolonged culture. ConclusionsCirculating neutrophils from arthritis patients resemble those from healthy controls, but joint fluid cells exhibit a network of changes, conserved across species, that implicate IFN{gamma} response and aging as complementary drivers of the synovial neutrophil phenotype. KEY MESSAGESO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LINeutrophils are central in the effector phase of inflammatory arthritis but their phenotypic heterogeneity in inflamed synovial fluid is poorly understood. C_LI What does this study add?O_LIRNA-seq and mass cytometry identify a hallmark phenotype of neutrophils in synovial fluid consisting of upregulated ICAM-1, HLA-DR, PD-L1, Fc receptors and CXCR4. C_LIO_LITranscriptomics highlight an IFN{gamma} response signature conserved across humans and mice. C_LIO_LIIn vitro experiments implicate aging and IFN{gamma} as complementary factors orchestrating the synovial fluid neutrophil phenotype. C_LI How might this impact on clinical practice or future developments?O_LIUnderstanding the specific features of neutrophils in the arthritic joint may disclose opportunities for safe therapeutic targeting of this lineage. C_LI

immunology↗